1 // Advanvced Part 3 about a really dumb investment strategy |
1 // Part 2 and 3 about a really dumb investment strategy |
2 //========================================================== |
2 //====================================================== |
3 |
3 |
4 object CW6c { |
4 //object CW6b { // for purposes of generating a jar |
5 |
5 |
6 |
6 |
7 //two test portfolios |
7 //two test portfolios |
8 |
8 |
9 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
9 val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU") |
10 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
10 val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI", |
11 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "GGP", "HCP") |
11 "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "HCP") |
12 |
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13 // (1) The function below should obtain the first trading price |
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14 // for a stock symbol by using the query |
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15 // |
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16 // http://ichart.yahoo.com/table.csv?s=<<symbol>>&a=0&b=1&c=<<year>>&d=1&e=1&f=<<year>> |
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17 // |
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18 // and extracting the first January Adjusted Close price in a year. |
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19 |
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20 |
12 |
21 import io.Source |
13 import io.Source |
22 import scala.util._ |
14 import scala.util._ |
23 |
15 |
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16 // (1) The function below takes a stock symbol and a year as arguments. |
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17 // It should read the corresponding CSV-file and reads the January |
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18 // data from the given year. The data should be collected in a list of |
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19 // strings for each line in the CSV-file. |
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20 |
24 def get_january_data(symbol: String, year: Int) : List[String] = |
21 def get_january_data(symbol: String, year: Int) : List[String] = |
25 Source.fromFile(symbol ++ ".csv").getLines.toList.filter(_.startsWith(year.toString)) |
22 Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines.toList.filter(_.startsWith(year.toString)) |
26 |
23 |
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24 |
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25 //test cases |
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26 //blchip_portfolio.map(get_january_data(_, 2018)) |
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27 //rstate_portfolio.map(get_january_data(_, 2018)) |
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28 |
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29 //get_january_data("GOOG", 1980) |
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30 //get_january_data("GOOG", 2010) |
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31 //get_january_data("FB", 2014) |
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32 |
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33 //get_january_data("PLD", 1980) |
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34 //get_january_data("EQIX", 2010) |
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35 //get_january_data("ESS", 2014) |
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36 |
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37 |
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38 // (2) From the output of the get_january_data function, the next function |
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39 // should extract the first line (if it exists) and the corresponding |
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40 // first trading price in that year with type Option[Double]. If no line |
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41 // is generated by get_january_data then the result is None; Some if |
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42 // there is a price. |
27 |
43 |
28 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
44 def get_first_price(symbol: String, year: Int) : Option[Double] = { |
29 val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None |
45 val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None |
30 data.map(_.split(",").toList(1).toDouble) |
46 data.map(_.split(",").toList(1).toDouble) |
31 } |
47 } |
32 |
48 |
33 get_first_price("GOOG", 1980) |
49 //test cases |
34 get_first_price("GOOG", 2010) |
50 //get_first_price("GOOG", 1980) |
35 get_first_price("FB", 2014) |
51 //get_first_price("GOOG", 2010) |
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52 //get_first_price("FB", 2014) |
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53 |
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54 /* |
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55 for (i <- 1978 to 2018) { |
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56 println(blchip_portfolio.map(get_first_price(_, i))) |
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57 } |
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58 |
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59 for (i <- 1978 to 2018) { |
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60 println(rstate_portfolio.map(get_first_price(_, i))) |
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61 } |
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62 */ |
36 |
63 |
37 |
64 |
38 // Complete the function below that obtains all first prices |
65 // (3) Complete the function below that obtains all first prices |
39 // for the stock symbols from a portfolio for the given |
66 // for the stock symbols from a portfolio (list of strings) and |
40 // range of years |
67 // for the given range of years. The inner lists are for the |
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68 // stock symbols and the outer list for the years. |
41 |
69 |
42 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = |
70 def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] = |
43 for (year <- years.toList) yield |
71 for (year <- years.toList) yield |
44 for (symbol <- portfolio) yield get_first_price(symbol, year) |
72 for (symbol <- portfolio) yield get_first_price(symbol, year) |
45 |
73 |
46 |
74 |
47 // test case |
75 //test cases |
48 val p_fb = get_prices(List("FB"), 2012 to 2014) |
76 //val p_fb = get_prices(List("FB"), 2012 to 2014) |
49 val p = get_prices(List("GOOG", "AAPL"), 2010 to 2012) |
77 //val p = get_prices(List("GOOG", "AAPL"), 2010 to 2012) |
50 |
78 |
51 val tt = get_prices(List("BIDU"), 2004 to 2008) |
79 //val tt = get_prices(List("BIDU"), 2004 to 2008) |
52 |
80 |
53 // (2) The first function below calculates the change factor (delta) between |
81 |
54 // a price in year n and a price in year n+1. The second function calculates |
82 //============================================== |
55 // all change factors for all prices (from a portfolio). |
83 // Do not change anything below, unless you want |
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84 // to submit the file for the advanced part 3! |
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85 //============================================== |
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86 |
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87 |
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88 // (4) The function below calculates the change factor (delta) between |
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89 // a price in year n and a price in year n + 1. |
56 |
90 |
57 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
91 def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = { |
58 (price_old, price_new) match { |
92 (price_old, price_new) match { |
59 case (Some(x), Some(y)) => Some((y - x) / x) |
93 case (Some(x), Some(y)) => Some((y - x) / x) |
60 case _ => None |
94 case _ => None |
61 } |
95 } |
62 } |
96 } |
63 |
97 |
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98 |
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99 // (5) The next function calculates all change factors for all prices (from a |
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100 // portfolio). The input to this function are the nested lists created by |
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101 // get_prices above. |
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102 |
64 def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] = |
103 def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] = |
65 for (i <- (0 until (data.length - 1)).toList) yield |
104 for (i <- (0 until (data.length - 1)).toList) yield |
66 for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j)) |
105 for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j)) |
67 |
106 |
68 |
107 |
69 // test case using the prices calculated above |
108 // test case using the prices calculated above |
70 val d = get_deltas(p) |
109 //val d = get_deltas(p) |
71 val ttd = get_deltas(tt) |
110 //val ttd = get_deltas(tt) |
72 |
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73 // (3) Write a function that given change factors, a starting balance and a year |
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74 // calculates the yearly yield, i.e. new balanace, according to our dump investment |
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75 // strategy. Another function calculates given the same data calculates the |
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76 // compound yield up to a given year. Finally a function combines all |
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77 // calculations by taking a portfolio, a range of years and a start balance |
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78 // as arguments. |
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79 |
111 |
80 |
112 |
81 def yearly_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = { |
113 // (6) Write a function that given change factors, a starting balance and an index, |
82 val somes = data(year).flatten |
114 // calculates the yearly yield, i.e. new balance, according to our dumb investment |
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115 // strategy. Index points to a year in the data list. |
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116 |
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117 def yearly_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = { |
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118 val somes = data(index).flatten |
83 val somes_length = somes.length |
119 val somes_length = somes.length |
84 if (somes_length == 0) balance |
120 if (somes_length == 0) balance |
85 else { |
121 else { |
86 val portion: Double = balance.toDouble / somes_length.toDouble |
122 val portion: Double = balance.toDouble / somes_length.toDouble |
87 balance + (for (x <- somes) yield (x * portion)).sum.toLong |
123 balance + (for (x <- somes) yield (x * portion)).sum.toLong |
88 } |
124 } |
89 } |
125 } |
90 |
126 |
91 def compound_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = { |
127 |
92 if (year >= data.length) balance else { |
128 // (7) Write a function compound_yield that calculates the overall balance for a |
93 val new_balance = yearly_yield(data, balance, year) |
129 // range of years where in each year the yearly profit is compounded to the new |
94 compound_yield(data, new_balance, year + 1) |
130 // balances and then re-invested into our portfolio. For this use the function and |
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131 // results generated under (6). The function investment calls compound_yield |
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132 // with the appropriate deltas and the first index. |
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133 |
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134 |
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135 def compound_yield(data: List[List[Option[Double]]], balance: Long, index: Int): Long = { |
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136 if (index >= data.length) balance else { |
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137 val new_balance = yearly_yield(data, balance, index) |
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138 compound_yield(data, new_balance, index + 1) |
95 } |
139 } |
96 } |
140 } |
97 |
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98 //yearly_yield(d, 100, 0) |
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99 //compound_yield(d.take(6), 100, 0) |
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100 |
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101 //test case |
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102 //yearly_yield(d, 100, 0) |
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103 //yearly_yield(d, 225, 1) |
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104 //yearly_yield(d, 246, 2) |
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105 //yearly_yield(d, 466, 3) |
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106 //yearly_yield(d, 218, 4) |
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107 |
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108 //yearly_yield(d, 100, 0) |
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109 //yearly_yield(d, 125, 1) |
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110 |
141 |
111 def investment(portfolio: List[String], years: Range, start_balance: Long): Long = { |
142 def investment(portfolio: List[String], years: Range, start_balance: Long): Long = { |
112 compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0) |
143 compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0) |
113 } |
144 } |
114 |
145 |
115 /* |
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116 val q1 = get_deltas(get_prices(List("GOOG", "AAPL", "BIDU"), 2000 to 2017)) |
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117 yearly_yield(q1, 100, 0) |
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118 yearly_yield(q1, 100, 1) |
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119 yearly_yield(q1, 100, 2) |
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120 yearly_yield(q1, 100, 3) |
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121 yearly_yield(q1, 100, 4) |
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122 yearly_yield(q1, 100, 5) |
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123 yearly_yield(q1, 100, 6) |
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124 |
146 |
125 investment(List("GOOG", "AAPL", "BIDU"), 2004 to 2017, 100) |
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126 val one = get_deltas(get_prices(rstate_portfolio, 1978 to 1984)) |
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127 val two = get_deltas(get_prices(blchip_portfolio, 1978 to 1984)) |
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128 |
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129 val one_full = get_deltas(get_prices(rstate_portfolio, 1978 to 2017)) |
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130 val two_full = get_deltas(get_prices(blchip_portfolio, 1978 to 2017)) |
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131 |
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132 one_full.map(_.flatten).map(_.sum).sum |
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133 two_full.map(_.flatten).map(_.sum).sum |
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134 |
147 |
135 //test cases for the two portfolios given above |
148 //test cases for the two portfolios given above |
136 |
149 |
137 //println("Real data: " + investment(rstate_portfolio, 1978 to 2017, 100)) |
150 //println("Real data: " + investment(rstate_portfolio, 1978 to 2018, 100)) |
138 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2017, 100)) |
151 //println("Blue data: " + investment(blchip_portfolio, 1978 to 2018, 100)) |
139 |
152 |
140 for (i <- 2000 to 2017) { |
153 //} |
141 println("Year " + i) |
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142 //println("Real data: " + investment(rstate_portfolio, 1978 to i, 100)) |
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143 //println("Blue data: " + investment(blchip_portfolio, 1978 to i, 100)) |
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144 println("test: " + investment(List("GOOG", "AAPL", "BIDU"), 2000 to i, 100)) |
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145 } |
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146 |
154 |
147 |
155 |
148 */ |
156 |
149 //1984 |
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150 //1992 |
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151 } |
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